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NASA NTRS2010

The Characterization of Deep Convective Cloud Albedo as a Calibration Target Using MODIS Reflectances

There are over 25 years of historical satellite data available to climate analysis. The historical satellite data needs to be well calibrated, especially in the visible, where there is no onboard calibration on operational satellites. The key to the vicarious calibration of historical satellites relies on invariant targets, such as the moon, Dome C, and deserts. Deep convective clouds (DCC) also show promise of being a stable invariant or predictable target viewable by all satellites, since they behave as solar diffusers. However DCC have not been well characterized for calibration. Ten years of well-calibrated MODIS is now available. DCC can easily be identified using IR thresholds, where the IR calibration can be traced to the onboard black-bodies. The natural variability of DCC albedo will be analyzed geographically and seasonally, especially difference of convection initiated over land or ocean. Functionality between particle size and ozone absorption with DCC albedo will be examined. Although DCC clouds are nearly Lambertion, the angular distribution of reflectances will be sampled and compared with theoretical models. Both Aqua and Terra MODIS DCC angular models will be compared for consistency. Normalizing angular geostationary DCC reflectances, which were calibrated against MODIS, with SCIAMACHY spectral reflectances and comparing them to MODIS DCC reflectances will inspect the usage of DCC albedos as an absolute calibration target.

Doelling, David R.↗

NASA NTRS2012

Detection Performance of Upgraded "Polished Panel" Optical Receiver Concept on the Deep-Space Network's 34 Meter Research Antenna

The development and demonstration of a "polished panel" optical receiver concept on the 34 meter research antenna of the Deep Space Network (DSN) has been the subject of recent papers. This concept would enable simultaneous reception of optical and microwave signals by retaining the original shape of the main reflector for microwave reception, but with the aluminum panels polished to high reflectivity to enable focusing of optical signal energy as well. A test setup has been installed on the DSN's 34 meter research antenna at Deep Space Station 13 (DSS-13) of NASA's Goldstone Communications Complex in California, and preliminary experimental results have been obtained. This paper describes the results of our latest efforts to improve the point-spread function (PSF) generated by a custom polished panel, in an attempt to reduce the dimensions of the PSF, thus enabling more precise tracking and improved detection performance. The design of the new mechanical support structure and its operation are described, and the results quantified in terms of improvements in collected signal energy and optical communications performance, based on data obtained while tracking the planet Jupiter with the 34 meter research antenna at DSS-13.

photon-bucket receiver↗

NASA NTRS2018

The Importance of Conducting Life Sciences Experiments on the Deep Space Gateway Platform

Over the last several decades important information has been gathered by conducting life science experiments on the Space Shuttle and on the International Space Station. It is now time to leverage that scientific knowledge, as well as aspects of the hardware that have been developed to support the biological model systems, to NASA's next frontier - the Deep Space Gateway. In order to facilitate long duration deep space exploration for humans, it is critical for NASA to understand the effects of long duration, low dose, deep space radiation on biological systems. While carefully controlled ground experiments on Earth-based radiation facilities have provided valuable preliminary information, we still have a significant knowledge gap on the biological responses of organisms to chronic low doses of the highly ionizing particles encountered beyond low Earth orbit. Furthermore, the combined effects of altered gravity and radiation have the potential to cause greater biological changes than either of these parameters alone. Therefore a thorough investigation of the biological effects of a cis-lunar environment will facilitate long term human exploration of deep space.

microgravity↗

NASA NTRS1997

The Solar-Stellar Connection (NAG5-6124: SOHO Guest Investigator Program)

The following is a final report from the SOHO Guest Investigator program to use the SUMER far-UV spectrometer to obtain imaging spectroscopy in support of the goals of the so-called "solar-stellar connection." In particular, a major emphasis was utilization of the long-slit time-resolved maps of the solar surface in bright far-UV emission lines to deduce how particular aspects of the temporally and spatially averaged line profiles trace back to individual structural features of the magnetically disturbed outer atmosphere; to help interpret the unresolved line profiles from high quality stellar observations (say, with the Space Telescope Imaging Spectrograph). The researchers served two tours of duty in the SOHO Operations Center as SUMER planners, during which time we conducted an extensive series of observing programs. These can be divided into three general categories: surface mapping, translimb spectroscopy, and active region diagnostics. We have analyzed some of the large volumes of data to the point where we have presented them in poster papers, and in invited papers at national and international meetings. Listed below are the titles of the preliminary publications we have written, including brief abstracts to indicate the main results. (1) Chromospheric structure and Dynamics-- Observations -- The chromosphere is a highly structured dynamic 'layer' of the solar outer atmosphere. Here, not only are the effects of mechanical heating first evident (moving upward in altitude from the deep photosphere), but also the amount of nonradiative energy deposited is far greater than in the albeit much hotter overlying transition region and corona. Further, the chromosphere is by far the thickest zone of the solar atmosphere with respect to the pressure scale height. A major goal of stellar astrophysics is to understand how the chromosphere is heated and why it adopts its peculiar structure. A cursory examination of solar filtergrams and high-resolution movies demonstrates that much of the chromospheric "action" must be occurring on fine spatial scales and short times; particularly in the cell interior transient brightenings, but also in the longer-lived network fragments. That regime of investigation is far removed from what one usually associates with "synoptic" measurements. Nevertheless, synoptic observations of chromospheric indices, filtergrams, and globally-averaged profile parameters not only can provide important insight concerning the crucial role of the cycle-variable part of the solar magnetic field; but they also can forge a key link with analogous measurements of the stars, where often the phenomena can be significantly exaggerated from the solar case, but high spatial resolution reconnaissance is not even a remote possibility. In addition to discussing the synoptic aspects of chromospheric structure and dynamics, I summarized new insights into the general problem of the solar chromosphere that have been obtained recently with the SUMER far-ultraviolet spectrometer on SOHO. (2) CO and the Temperature Structure of the Solar Atmosphere -- The surface layers of the Sun provide a crucial boundary condition for many of the processes that occur in the deep interior. The stratification of the outer solar atmosphere once was thought to be well understood. However, studies of thermally sensitive molecular absorptions in the infrared revealed puzzling anomalies. Strong lines of the CO fundamental vibration-rotation bands near 5 microns showed very cool temperatures at the extreme limb, and remarkable off-limb emissions extending well into the supposedly hot chromosphere. The conflicting pictures of the photosphere/chromosphere interface, from the widely separated wavelength regimes, has raised suspicions that those "layers" of the atmosphere are much more inhomogeneous than previously suspected. One proposal is that the low chromosphere is dominated by cool gas, the "COmosphere," which is threaded by a network of persistent small-scale hot magnetic filaments and occasionally disrupted by localized acoustic disturbances. The COmosphere is capped by the merged fields of the network elements in the chromospheric "canopy." (3) Translimb Spectroscopy with SOHO/SUMER -- We have used SUMER to obtain deep exposures of the 1300-1400 A spectrum, at the extreme limb and off-limb. Previous "translimb" studies in the thermal infrared had revealed remarkable extensions of cold material (T is approximately equal to 3000 K)-traced by carbon monoxide emission lines-into the heart of the hot chromosphere. A main objective of our program was to search for corresponding far-UV signatures of the "thermally-bifurcated" low chromosphere; for example, radiatively fluoresced emissions of the CO A-X 4th-positive system (collisional excitation would be negligible in cold gas). We conducted two separate observing programs with SUMER. Both made use of the 1 inch-diameter circular aperture, translated across the limb in the minimum motor step increments of 0."375, along the central meridian in the Northern polar coronal hole. The first program executed for nine hours beginning 19UT 25 Oct 1996. The full wavelength range was 1340-1400 A. It was recorded in two overlapping segments, placing key regions of the spectrum alternately on the KBr and bare parts of the detector, to help isolate 2nd-order features. Each segment was integrated for 500 s, and 32 pairs were obtained to span a 12" swath centered on the optical limb. The second program was conducted 00-09UT 01 Dec 1996. It consisted of a single wavelength setting (1300-1340 A) with exposure time 500 s, but twice the spatial coverage of the earlier series: 64 steps, for a total displacement of 24". The strong chromospheric resonance lines of atomic oxygen (1302-1305 A) and ionized carbon (1334-1335 A) were observed on the bare part of the MCP camera.

Ayres, Thomas R.↗

DOE OSTI2022

Deep learning potential of mean force between polymer grafted nanoparticles

Grafting polymer chains on the surfaces of nanoparticles is a well-known route to control their self-assembly and distribution in a polymer matrix. A wide variety of self-assembled structures are achieved by changing the grafting patterns on the surface of an individual nanoparticle. However, an accurate estimation of the effective potential of mean force between a pair of grafted nanoparticles that determines their assembly and distribution in a polymer matrix is an outstanding challenge in nanoscience. We address this problem via deep learning. As a proof of concept, here we report a deep learning framework that learns the interaction between a pair of single-chain grafted spherical nanoparticles from their molecular dynamics trajectory. Subsequently, we carry out the deep learning potential of mean force-based molecular simulation that predicts the self-assembly of a large number of single-chain grafted nanoparticles into various anisotropic superstructures, including percolating networks and bilayers depending on the nanoparticle concentration in three-dimensions. The deep learning potential of mean force-predicted self-assembled superstructures are consistent with the actual superstructures of single-chain polymer grafted spherical nanoparticles. This deep learning framework is very generic and extensible to more complex systems including multiple-chain grafted nanoparticles. Finally, we expect that this deep learning approach will accelerate the characterization and prediction of the self-assembly and phase behaviour of polymer-grafted and unfunctionalized nanoparticles in free space or a polymer matrix.

36 MATERIALS SCIENCE↗

NASA NTRS1997

Geotail MCA Plasma Wave Investigation Data Analysis

The primary goals of the International Solar Terrestrial Physics/Global Geospace Science (ISTP/GGS) program are identifying, studying, and understanding the source, movement, and dissipation of plasma mass, momentum, and energy between the Sun and the Earth. The GEOTAIL spacecraft was built by the Japanese Institute of Space and Astronautical Science and has provided extensive measurements of entry, storage, acceleration, and transport in the geomagnetic tail and throughout the Earth's outer magnetosphere. GEOTAIL was launched on July 24, 1992, and began its scientific mission with eighteen extensions into the deep-tail region with apogees ranging from around 60 R(sub e) to more than 208 R(sub e) in the period up to late 1994. Due to the nature of the GEOTAIL trajectory which kept the spacecraft passing into the deep tail, GEOTAIL also made 'magnetopause skimming passes' which allowed measurements in the outer magnetosphere, magnetopause, magnetosheath, bow shock, and upstream solar wind regions as well as in the lobe, magnetosheath, boundary layers, and central plasma sheet regions of the tail. In late 1994, after spending nearly 30 months primarily traversing the deep tail region, GEOTAIL began its near-Earth phase. Perigee was reduced to 10 R(sub e) and apogee first to 50 R(sub e) and finally to 30 R(sub e) in early 1995. This orbit provides many more opportunities for GEOTAIL to explore the upstream solar wind, bow shock, magnetosheath, magnetopause, and outer magnetosphere as well as the near-Earth tail regions. The WIND spacecraft was launched on November 1, 1994 and the POLAR spacecraft was launched on February 24, 1996. These successful launches have dramatically increased the opportunities for GEOTAIL and the GGS spacecraft to be used to conduct the global research for which the ISTP program was designed. The measurement and study of plasma waves have made and will continue to make important contributions to reaching the ISTP/GGS goals and solving the significant problems of sun-earth connections. Plasma waves are involved in the energization and de-energization of plasma and energetic particles via numerous wave-particle interaction processes. Plasma waves in many instances are the source for the heating or cooling of the particles. They can cause particle precipitation by scattering particles into the loss cone. They move particles across boundaries in mass and energy dependent ways. Identifying the waves and the instabilities which produce them are thus crucial for understanding the plasma processes. Wave-particle interaction processes are especially important at various boundaries between the different regions of geospace including the bow shock, magnetopause, and interfaces in the geomagnetic tail between the magnetosheath, lobe, plasmasheet, boundary layers, and neutral sheet. In addition to identifying the characteristics of the instabilities and generation mechanisms encountered, plasma wave measurement are used in conjunction with other fields and particle measurements to identify the region of space the spacecraft is in or the boundary that is being crosed.

Anderson, Roger R.↗

DOE OSTI2024

Three-dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep-learning techniques

Using multiple geophysical methods has become a prevailing approach in numerous geophysical applications to investigate subsurface structures and parameters. These multimethod-based exploration strategies have the potential to greatly diminish uncertainties and ambiguities encountered during geophysical data analysis and interpretation. One of the applications is the cooperative inversion of airborne magnetic and gravity gradient data for the interpretation of data obtained in mineral, oil and gas, and geothermal explorations. In this paper, a unified cooperative inversion framework is designed by combining the standard separate inversions with a deep neural network (DNN), which serves as the link between different types of data. A well-trained DNN takes the separately inverted susceptibility and density models as the inputs and provides improved models that will be used as the initial models of deterministic inversions. A two-round iteration strategy is adopted to guarantee the reasonability of the recovered models and overall efficiency of the inversion. In addition, this deep-learning (DL)-based framework demonstrates excellent generalization abilities when tested on models that are entirely distinct from the training data sets. The framework can easily incorporate multiphysics without necessitating any structural changes to the network. Synthetic experiments validate that our DL-based method outperforms conventional separate inversions and cross-gradient-based joint inversion in view of the accuracy of the recovered models and inversion efficiency. Successful application to field data further verifies the effectiveness of our DL-based method.

Geochemistry & Geophysics↗

NASA NTRS1986

System concepts and design examples for optical communication with planetary spacecraft

Systems concepts for optical communication with future deep-space (planetary) spacecraft are described. These include not only the optical transceiver package aboard the distant spacecraft, but the earth-vicinity optical-communications receiving station as well. Both ground-based, and earth-orbiting receivers are considered. Design examples for a number of proposed or potential deep-space missions are then presented. These include an orbital mission to Saturn, a Lander and Rover mission to Mars, and an astronomical mission to a distance of 1000 astronomical units.

Lesh, James R.↗

NASA NTRS1993

An Optical Study of the Faint End of the Stellar Luminosity Function

Herbst, W.↗

NASA NTRS1985

Deep space observations of the east-west asymmetry of solar energetic storm particle events - Voyagers 1 and 2

It has been well established that solar flare shock waves, propagating through the interplanetary medium, accelerate ambient energetic particles, giving rise to the formation of energetic storm particle (ESP) intensity enhancements. However, the acceleration mechanism which is responsible for the generation of ESP events is still under investigation. In the present investigation, energetic proton observations during solar flare ESP events made with the aid of the Voyagers 1 and 2 deep space probes are employed as a basis to examine further the acceleration processes responsible for the generation of ESP events under different 'interplanetary magnetic field-shock front' configurations. It is found that large ESP proton intensity enhancements are superimposed on the ambient solar energetic particle population for solar flare sites to the east of the sun-spacecraft medidian.

Sarris, E. T.↗

DOE OSTI2025

Integrating Analytical Solutions and U-Net Model for Predicting Groundwater Contaminant Plumes in Pump-and-Treat Systems

Pump-and-treat (P&T) is a common technique for groundwater remediation involving the extraction and treatment of contaminated water above ground. Optimizing the design and operation of the P&T well network is essential for maximizing the system’s effectiveness and efficiency. However, this optimization often necessitates many model evaluations, leading to computationally demanding tasks. This study introduces a novel approach that integrates analytical solutions for groundwater dynamics with the U-Net (Ronneberger et al., 2015) deep learning framework to predict groundwater contaminant plume migration under dynamic pumping conditions. By incorporating the Thiem equation (Thiem, 1906) into the input preprocessing, the U-Net model transforms sparse well data into a continuous spatial field that captures the hydraulic impacts of pumping activities. This integration enables the model to leverage both deep learning capabilities and classical physics-based groundwater theories, enhancing prediction accuracy and computational efficiency. These advancements can facilitate rapid, large-scale evaluations of P&T optimization simulations, allowing for timely and effective decision-making in well placement and system management. We demonstrate the model's robust performance across both simplified transient 2D models and a more complex 3D heterogeneous site model at the 200 West P&T facility at the Hanford Site. The U-Net-based model offers substantial computational advantages, reducing simulation times significantly compared to full physics-based models and providing a powerful tool for rapid site evaluation and P&T system optimization, such as evaluating alternative P&T well network designs. Our findings highlight the potential of advanced machine learning models to significantly enhance the efficiency and sustainability of groundwater remediation efforts, offering a novel application of U-Net architecture in environmental science.

Pump-and-treat↗

DOE OSTI2020

Adaptive Activation Functions Accelerate Convergence in Deep and Physics-informed Neural Networks

We employ adaptive activation functions for regression in deep and physics-informed neural networks (PINNs) to approximate smooth and discontinuous functions as well as solutions of linear and nonlinear partial differential equations. In particular, we solve the nonlinear Klein-Gordon equation, which has smooth solutions, the nonlinear Burgers equation, which can admit high gradient solutions, and the Helmholtz equation. We introduce a scalable hyper-parameter in the activation function, which can be optimized to achieve best performance of the network as it changes dynamically the topology of the loss function involved in the optimization process. The adaptive activation function has better learning capabilities than the traditional one (fixed activation) as it improves greatly the convergence rate, especially at early training, as well as the solution accuracy. To better understand the learning process, we plot the neural network solution in the frequency domain to examine how the network captures successively different frequency bands present in the solution. We consider both forward problems, where the approximate solutions are obtained, as well as inverse problems, where parameters involved in the governing equation are identified. Our simulation results show that the proposed method is a very simple and effective approach to increase the efficiency, robustness and accuracy of the neural network approximation of nonlinear functions as well as solutions of partial differential equations, especially for forward problems. We theoretically prove that in the proposed method, gradient descent algorithms are not attracted to suboptimal critical points or local minima.

machine leaning, Bad minima, Inverse problems, Phy↗

NASA NTRS1994

An optical study of the faint end of the stellar luminosity function

We implement a new method by which to study the faint end of the field star luminosity function. The method relies on deep, multicolor photometry of fields projected against highly obscured, nearby molecular clouds. The clouds act as nearby opaque screens and delimit a well-defined survey volume which is in principle free of the problem of distinguishing nearby, intrinsically faint dwarf stars from more distant red giants. This study is based upon deep photographic and CCD photometry at optical (V, R, I) bandpasses toward the most highly obscured portions of the Taurus and Ophiuchus molecular clouds. The total volume delimited by the clouds is approximately 200 cu pc. Within this region our survey is complete for all stars brighter than M(sub V) = 16-17 mag; at R and I, the survey is complete down to the lowest mass stars capable of sustaining core hydrogen burning. We estimate the faint end of the field star luminosity function for the composite Taurus and Ophiuchus foreground sample and find that it resembles the local luminosity function down to M(sub V) approx. 16. At still fainter magnitudes we find more stars than do photometric parallex studies of the polar regions. This difference widens dramatically if even the simplest correction for incompleteness is applied to our data. We therefore tentatively conclude that the luminosity function rises beyond M(sub V) approx. 16; even if we discard our attempts to correct for incompleteness in the faintest magnitude bins, the luminosity function at least remains flat for the lowest mass stars. Our provisional finding that the luminosity function rises beyond its well-known peak at M(sub V) approx. 12-13, implies that the initial mass function (IMF) probably rises beyond the turnover point associated with this peak. Even if our most conservative estimate for the faint end of the luminosity function is used-in which no corrections are made for incompleteness-the IMF must at least remain flat down to the edge of the hydrogen-burning main sequence.

Jarrett, T. H.↗

NASA NTRS2012

Microchip Non-Aqueous Capillary Electrophoresis (MicronNACE) Method to Analyze Long-Chain Primary Amines

A protocol was developed as a first step in analyzing the complex organic aerosols present on Saturn's moon Titan, as well as the analogues of these aerosols (tholins) made on Earth. Labeling of primary amines using Pacific Blue succinimidyl ester is effected in ethanol with 25 mM triethylamine to maintain basic conditions. This reaction is allowed to equilibrate for at least one hour. Separation of the labeled primary amines is performed in ethanol with 1.05 M acetic acid, and 50 mM ammonium acetate in a commercial two-layer glass device with a standard crossmicrochannel measuring 50 microns wide by 20 microns deep. Injection potentials are optimized at 2 kV from the sample (negative) to the waste well (positive), with slight bias applied to the other two wells ( 0.4 and 0.8 V) to pinch the injection plug for the 30-s injection. Separation is performed at a potential of 5 kV along the channel, which has an effective separation distance of 7 cm. The use of ethanol in this method means that long-chain primary amines can be dissolved. Due to the low pH of the separation buffer, electro-osmotic flow (EOF) is minimized to allow for separation of both short-chain and longchain amines. As the freezing point of ethanol is much lower than water, this protocol can perform separations at temperatures lower than 0 C, which would not be possible in aqueous phase. This is of particular importance when considering in situ sampling of Titan aerosols, where unnecessary heating of the sample (even to room temperature) would lead to decomposition or unpredictable side reactions, which would make it difficult to characterize the sample appropriately.

Willis, Peter A.↗

NASA NTRS1996

Geotail MCA Plasma Wave Investigation Data Analysis

The goals of this program include identifying, studying, and understanding the source, movement, and dissipation of plasma mass, momentum, and energy between the Sun and Earth. The GEOTAIL spacecraft was built by the Japanese Institute of Space and Aeronautical Science and has provided extensive measurements of entry, storage, acceleration, and transport in the geomagnetic tail. Due to the GEOTAIL trajectory, which kept the spacecraft passing into the deep tail, GEOTAIL also made 'magnetopause skimming passes' which allowed measurements in the outer magnetosphere, magnetopause, bow shock, and upstream solar wind regions as well as in the lobe, magnetosheath, boundary layers, and central plasma sheet regions of the tail. In late 1994, after spending nearly 30 months primarily traversing the deep tail region, GEOTAIL began its near Earth phase where apogee was reduced first to about 50 Re and later to 30 Re and perigee was decreased to about 10 Re. The WIND spacecraft was launched on November 1, 1994, and the POLAR spacecraft was launched on February 24, 1996. These successful launches have dramatically increased the opportunities for GEOTAIL and the GGS spacecraft to conduct global research.

Anderson, Roger R.↗

DOE OSTI2021

Atomic Layer Deposition with TiO2 for Enhanced Reactivity and Stability of Aromatic Hydrogenation Catalysts

Hydrogenation of aromatic molecules in fossil- and bio-derived fuels is essential for decreasing emissions of harmful combustion products and addressing growing concerns around urban air pollution. In this work, we used atomic layer deposition to significantly enhance the hydrogenation performance of a conventional supported Pd catalyst by applying an ultrathin coating of TiO2 in a scalable powder coating process. The TiO2-coated catalyst showed substantial gains in the conversion of multiple aromatic molecules, including a 5-fold improvement in turnover frequency versus the uncoated catalyst in the hydrogenation of naphthalene. This activity enhancement was maintained upon scaling the coating synthesis process from 3 to 100 g. Based on the results from Xray photoelectron spectroscopy, X-ray absorption spectroscopy, and computational modeling, the activity enhancement was attributed to ensemble effects resulting from partial TiO2 coverage of the Pd surface rather than fundamental changes to the Pd electronic structure. Additional durability testing confirmed that the TiO2 coating improved the thermal and hydrothermal stability of the catalyst as well as tolerance toward sulfur impurities in the reactant stream. Using an economic model of an industrial deep hydrogenation process, we found that an increase in catalyst activity or lifetime of 2× would justify even a relatively high estimate for the cost of TiO2 atomic layer deposition coatings at scale

atomic layer↗

DOE OSTI2020

Completion design improvement using a deep convolutional network

Maximizing stimulated natural and hydraulic fracture network is one of the primary hydraulic fracturing concerns for economic production from a horizontal shale gas well. Geomechanical facies and preexisting fractures in each stage are identified based on similarities in formation characteristics to optimize the locations of perforation clusters. This often requires analyzing large volumes of drilling, Logging While Drilling (LWD) and Measurement While Drilling (MWD) data. In this paper, we develop a methodology that calculates the mechanical specific energy (MSE) using real-time drill string acceleration signals directly from its definition. High resolution vibration signals have been collected using a tri-axial accerlometer, which was an auxiliary tool included in acoustic borehole imager. This technique provides a cost-efficient solution for engineered completion design. Furthermore, we adopt deep Convolutional Neural Network (CNN) with signal processing to build a data pipeline that effectively extracts patterns from dynamic acceleration signals for rock lateral MSE classification. First, we apply discrete wavelet transform and Short-Time Fourier Transform (STFT) for signal denoising and pattern recognition. Then we construct an image dataset using multi-scale image fusion at pixel level from 3 sensor channels, including axial, lateral acceleration spectrograms and zero-padded revolutions per minute (RPM). The resulted RGB image dataset includes 4,000 images of 5 MSE ranges with various rock strength conditions. Our results demonstrate that the proposed deep learning model can achieve more than 90% classification accuracy. The deep learning results, as a reference source, were applied in selected Marcellus Shale Energy and Environmental Lab (MSEEL) wells engineered completion located in the Marcellus shale gas site.

03 NATURAL GAS↗

NASA NTRS2023

A Review of the Safety of Selective Serotonin Reuptake Inhibitors for Long Duration Spaceflight

Introduction: As humankind ventures further into the depths of space, planning is already underway for long-duration exploration missions that will test the bounds of human performance. Deep space travel will include added risk related to stressors from the isolated, confined, and extreme (ICE) environment that lies outside the boundaries of low-earth orbit. Currently, selective serotonin reuptake inhibitors (SSRIs) are considered the gold standard treatment for many mental health diagnoses including anxiety and depression; however, SSRIs are also associated with several undesired side effects. The utility of non-pharmacologic therapies for the management of behavioral health conditions has not yet been fully explored. Methods: A comprehensive literature search was performed using PubMed and relevant articles pertaining to the psychological impacts of ICE environments, use of SSRIs in spaceflight, side effects associated with SSRIs, and non-pharmacologic treatments for anxiety and depression were reviewed. Over 100 studies were reviewed in total. Results: Reduced bone mineral density, impaired hemostatic function, significant individual variability resulting from gene polymorphisms, and drug-drug interactions are well described adverse effects of SSRIs that may complicate their operational use in the deep space environment. Many non-pharmacologic therapies have been utilized with success for the management of behavioral health conditions in the terrestrial environment that may show promise for long duration missions. Discussion: Although SSRIs have long been considered standard of care treatment for many behavioral health conditions, we cannot trivialize the risk that prolonged pharmacologic therapy may pose. The need to mitigate these risks by exploring alternative non-pharmacologic therapies has never been more relevant.

Charles H Dukes↗